结构性创新对组织绩效的影响机制研究

基于生态位理论,深入研究了结构性创新对组织绩效的影响机制,考察知识解构/知识重构的中介作用和知识共享/资源获取的调节作用。针对221个制造型企业的多时点研究发现：结构性创新正向影响组织绩效,知识解构和知识重构在其中起中介作用;知识共享调节结构性创新与知识解构/知识重构间的关系,也通过知识解构/知识重构调节结构性创新与组织绩效的间接关系;资源获取调节结构性创新与知识重构间的关系,也通过知识重构调节结构性创新与组织绩效的间接关系。     

Towards medical knowmetrics: representing and computing medical knowledge using semantic predications as the knowledge unit and the uncertainty as the knowledge context

In China, Prof. Hongzhou Zhao and Zeyuan Liu are the pioneers of the concept “knowledge unit” and “knowmetrics” for measuring knowledge. However, the definition on “computable knowledge object” remains controversial so far in different fields. For example, it is defined as (1) quantitative scientific concept in natural science and engineering, (2) knowledge point in the field of education research, and (3) semantic predications, i.e., Subject-Predicate-Object (SPO) triples in biomedical fields. The Semantic MEDLINE Database (SemMedDB), a high-quality public repository of SPO triples extracted from medical literature, provides a basic data infrastructure for measuring medical knowledge. In general, the study of extracting SPO triples as computable knowledge unit from unstructured scientific text has been overwhelmingly focusing on scientific knowledge per se. Since the SPO triples would be possibly extracted from hypothetical, speculative statements or even conflicting and contradictory assertions, the knowledge status (i.e., the uncertainty), which serves as an integral and critical part of scientific knowledge has been largely overlooked. This article aims to put forward a framework for Medical Knowmetrics using the SPO triples as the knowledge unit and the uncertainty as the knowledge context. The lung cancer publications dataset is used to validate the proposed framework. The uncertainty of medical knowledge and how its status evolves over time indirectly reflect the strength of competing knowledge claims, and the probability of certainty for a given SPO triple. We try to discuss the new insights using the uncertainty-centric approaches to detect research fronts, and identify knowledge claims with high certainty level, in order to improve the efficacy of knowledge-driven decision support.

     

一种基于知识地图集的知识管理系统模型框架

在分析知识管理、知识管理系统(KMS)的含义和知识地图集技术的特点的基础上，提出了一种基于知识地图集的KMS模型框架，并且分析了该模型框架中知识地图集的组成及功能，讨论了KMS中知识地图集和知识存储之间的关系。依据该模型框架，组织易于构建知识管理系统，实现知识资源的共享与充分运用。最后，通过一个实例分析进一步说明了该模型框架的应用。     

Knowledge Composition and Its Influence on New Product Development Performance in the Big Data Environment

Product innovation is regarded as a primary means for enterprises to maintain their competitive advantage. Knowledge transfer is a major way that enterprises access knowledge from the external environment for new product innovation. Knowledge transfer may face the risk of infringement of the intellectual property rights of other enterprises and the termination of licensing agreements by the knowledge source. Enterprises must develop independent innovation knowledge at the same time they profit from knowledge transfers. Therefore, new product development by an enterprise usually consists of three types of new knowledge: big data knowledge transferred from big data knowledge providers, private knowledge transferred from other enterprises, and new knowledge developed independently by an enterprise in the big data environment. To find what the influences of different types of knowledge are on new product development (NPD) performance, a model is presented that maximizes the expected NPD performance. The results show that the greater the weight of independent innovation knowledge, the greater the performance of NPD. Enterprises tend to transfer knowledge from the external environment when the research and development (R&D) investment is much higher, and enterprises will speed up independent innovation when independent innovation knowledge is expected to bring a larger market share. The model can help enterprises to determine knowledge composition, the scale of R&D investment and predict the performance of NPD.     

Managing distributed manufacturing knowledge through multi-perspective modelling for semantic web applications

The development and maintenance of semantic web (SW) means that collaborative manufacturing systems are faced with increasing challenges caused by the growing difficulty in managing distributed manufacturing knowledge. This paper presents a multi-perspective modelling approach to systematically manage distributed manufacturing knowledge on the SW. Considering knowledge engineering as a cyclic and constructive modelling process, a multi-perspective knowledge modelling process is proposed to evolve along knowledge elicitation, engineering modelling, UML-based object modelling, OWL-based ontology modelling, knowledge formalisation and OWL-QL assisted knowledge verification activities. The proposed approach is viewed as a promising knowledge management method that facilitates the implementation of computer supported cooperative work (CSCW) in distributed manufacturing for SW applications by integrating the industrial, UML enabled software engineering techniques into recent ontology-based knowledge engineering process. The feasibility of knowledge management through multi-perspective modelling is manifested using the manufacturing ontology for manufacturing electronic connectors.     

Time Optimization of Multiple Knowledge Transfers in the Big Data Environment

In the big data environment, enterprises must constantly assimilate big data knowledge and private knowledge by multiple knowledge transfers to maintain their competitive advantage. The optimal time of knowledge transfer is one of the most important aspects to improve knowledge transfer efficiency. Based on the analysis of the complex characteristics of knowledge transfer in the big data environment, multiple knowledge transfers can be divided into two categories. One is the simultaneous transfer of various types of knowledge, and the other one is multiple knowledge transfers at different time points. Taking into consideration the influential factors, such as the knowledge type, knowledge structure, knowledge absorptive capacity, knowledge update rate, discount rate, market share, profit contributions of each type of knowledge, transfer costs, product life cycle and so on, time optimization models of multiple knowledge transfers in the big data environment are presented by maximizing the total discounted expected profits (DEPs) of an enterprise. Some simulation experiments have been performed to verify the validity of the models, and the models can help enterprises determine the optimal time of multiple knowledge transfer in the big data environment.     

基于3M特征的设计知识表达模型

针对目前支持创新设计的知识多是分类表达和管理,缺乏统一的知识表达和管理模型的问题,提出了一种基于3M（multi-attribute multi-dimensional multi-hierarchy,多属性多维度多层次）特征的知识统一表达与管理方法。根据支持创新设计的知识需求,将知识属性分为创新属性和基本属性两大类：创新属性是对知识内容的抽象化提取并实现知识间的多属性关联,包括知识的功能、输入输出流、TRIZ原理、领域属性;基本属性是对多学科知识物理属性的具体表述,包含背景、功能、原理、结构属性。通过建立基于知识创新属性和基本属性统一架构的知识表达模板,实现对不同类型知识的综合表达与交叉迁移,并根据该方法构建了相应知识库原型系统。以核反应堆堆下结构改进设计为例,说明了知识库的应用流程。结果表明此知识模型能够实现对设计知识的统一表达和管理,有利于知识的查找和应用,能有效地辅助设计者进行创新设计。     

A knowledge accumulation approach based on bilayer social wiki network for computer-aided process innovation

Under the fierce competition, manufacturing companies pay more attention to innovation and the knowledge that enables innovation. Manufacturing process innovation is a knowledge-intensive activity, and efficient knowledge accumulation is the prerequisite and basis for computer-aided process innovation (CAPI). Hence, this research aims to build an open knowledge accumulation approach to obtain organised and refined process innovation knowledge (PIK). By considering the similarity of PIK network with biological neural network and combining the technical characteristics of social network with wiki, a novel PIK accumulation schema based on bilayer social wiki network is proposed. In social wiki network environment, PIK is accumulated in public knowledge space through participants’ social interactions and knowledge activities. The process of knowledge fusion is investigated to form the preliminary knowledge containing collective intelligence, and the mechanisms of collaborative editing and collaborative evolution are studied to refine the knowledge. The outcomes of this study lay the foundation for knowledge application of CAPI. Finally, a case study is presented to demonstrate the applicability of the proposed approach.     

Collaboration structure and knowledge diffusion in Turkish management academia

This article proposes a conceptual framework to study diffusion of knowledge via collaborative social interactions. The framework primes deliberation on (i) nature of knowledg, (ii) chain of knowledge process, and (iii) modes of knowledge transfer while examining mechanisms of knowledge diffusion and collaboration structure. Within such a differentiation scheme while information is considered as a form of filtered data within a context of relevancies, knowledge is considered as a systematically processed information that is bound to individual or collective actions and praxis. The framework is applied employing an empirical research method based on meta-network analysis. The examplary case traces how management sciences related knowledge is diffused and what collaboration structures are exhibited by Turkish management academia from 1920s until 2008. Results from knowledge diffusion models which have been devised and tested in this study hint that management knowledge within local publications follows patterns of information diffusion rather than patterns of knowledge transfer found elsewhere. On the other hand, it is seen that cognitive demand of publishing in citation indexed global journals have given way to cohesive collaborating teams as mean of collaborative knowledge production and transfer.     

Depreciation and transfer of knowledge: an empirical exploration of a shipbuilding process

It is well known from the psychological literature that knowledge acquisition (learning) and knowledge depreciation (unlearning) are governed by quite different rules. We propose a new learning curve model that measures acquisition of knowledge and depreciation in a single framework but governed by two different rules. The model considers that knowledge is acquired both by doing and from the experience of others. It also assumes that knowledge depreciates, if it does, continuously over time. We empirically demonstrate the applicability of our model using a dataset based on the construction of homogeneous ships in sixteen different shipways of a shipyard. It is observed that learning by doing (or direct learning) is the major source of productivity growth. Learning from others (or indirect learning) is also found to be sizable. The potential contribution to productivity of indirect learning is about 40% of the contribution of direct learning. It is also observed that knowledge indeed depreciates and it does so rapidly. Only about three quarters of knowledge available at the beginning of a month would remain by the end of the month due to forgetting. Therefore, if depreciation of knowledge or indirect learning (the transfer of knowledge) in a learning curve analysis is ignored, estimation of production rates and costs would be seriously biased.     

External and Internal Knowledge in the Knowledge Generation Function

This paper explores the role of internal and external knowledge in the generation of new technological knowledge. It implements the notion of recombinant knowledge generation function with the appreciation of: (i) the complementary—as opposed to supplementary—role of external knowledge and (ii) the role of the size and composition of the internal stock of knowledge. The empirical section is based upon a panel of companies listed on the main European financial markets for the period 1995–2006. The econometric analysis is based on simultaneous equations. The results confirm that R&D efforts and external knowledge are indispensable inputs into the generation of new technological knowledge.     

Knowledge integration and sharing for complex product development

Product development is a highly creative and knowledge-intensive process that involves extensive information and knowledge exchange and sharing among geographically distributed teams and developers. How to best integrate such heterogeneous product knowledge has become an extremely important knowledge management (KM) subject associated with product development. Product development knowledge integration and sharing is becoming a key issue in the enterprise KM. This paper addresses the challenges of product development knowledge integration and sharing during product development. The aim of this research work effort is to develop a method to enhance the integration and sharing of product knowledge during the development phase. This study presents a systematic approach to developing knowledge integration and sharing for product development. The proposed approach includes the steps for designing a framework of product development knowledge sharing, developing representation model for product development knowledge, designing product development knowledge sharing process, designing product development knowledge integration ontology, developing knowledge integration and sharing method for product development based on ontology, and implementation of product development knowledge integration and sharing method. The proposed method could bring out an efficient and proactive way for knowledge integration and sharing among product developers in the product development process.     

Review on Electronic Knowledge Reservoirs(EKRs)

The application of knowledge management system to manage the internal knowledge of organization has become the effective means,the electronic knowledge reservoirs( EKRs) have become an increasingly popular tool within various knowledge management information systems. In this paper,the concept,model,function of the EKRs,and the usage of the EKRs from the perspective of knowledge contribution and knowledge seeking are reviewed. This paper proposes to study EKRs from a more comprehensive view and obtain data from different industries.     

CMDNET中异地调用系统的环境及实现

介绍了现代设计网络（ＣＭＤＮＥＴ）组织以及在ＣＭＤＮＥＴ网络组织上异地调用环境和知识资源的建设，以轴承动／静特性和大型汽轮发电机组的稳定性分析为对象，编制了供远程异地调用的分析系统，为现代设计中分布式知识资源的获到和异地设计中知识资源远程调用的建设提供基础和借鉴。     

Study on Case—Based Fixture Design

Fixture is an important manufacturing activity.Afixture design system based on case-based reasoning(CBR) is proposed in this paper.A nwe method of case representation on the basis of fixture function is presented,where the case representation is constituted of workpiece knowledge,processing feature knowledge,and fixture feature knowledge.Running the prototype system shows that the knowl-edge representation method ,using cases,is a better way to transform and explain the design knowl-edge.     

一类基于认知心理特征的知识发现新模型

为克服数据挖掘过程中的"数据海量,算法复杂"的困扰,建立了两个用于在知识发现系统与过程中模拟认知心理特征的协调器--启发型协调器和维护型协调器,从而实现了系统自主地发现知识短缺和进行知识库的实时维护;创建了双库协同机制,它揭示了数据库与知识库在特定构造下,两个范畴间的等价关系(即结构对应定理);并将这两个协调器和双库协同机制融入经典的数据库中的知识发现(KDD)过程模型,诱导出新的知识发现过程模型--KDD和基于数据库和知识库双库数据挖掘(KD (D&K))过程模型,实现了"定向搜索"与"定向挖掘".最后通过实例验证了其有效性与先进性.     

A holistic view of knowledge integration in collaborative supply chains

New product development (NPD) projects offer a unique opportunity to examine knowledge integration themes in a collaborative network. We propose a finer grained view of knowledge integration mechanisms in collaborative supply chains. Specifically, we propose two different types of mechanisms that are in play within a collaborative supply chain; short-term knowledge sharing and iterative knowledge enrichment. Using data from a large and diverse set of 432 NPD projects, we investigate the effects of knowledge sharing and enrichment between firms and their collaborative network partners, on product concept effectiveness and process performance. Our findings suggest that knowledge sharing and enrichment are significant mechanisms for enterprise-wide knowledge integration in collaborative networks. In addition, upstream knowledge sharing and enrichment has a significant influence on both product concept effectiveness and manufacturing process performance, over and above the effects of downstream knowledge sharing and enrichment. The relationship of upstream and downstream knowledge sharing and enrichment on product concept effectiveness and process performance had varying effects based on the contexts of product type, stage in the product life cycle and project size, indicating a context-specific influence of knowledge strategies. The implication of our results on academic theory and managerial practice is offered.     

The influence of different knowledge workers on innovation strategy and product development performance in small and medium-sized enterprises

Despite significant interest on the topic of knowledge workers, the understanding of how they influence certain aspects of firm innovativeness remains limited. In particular, while different types of knowledge workers exist, their particular synergistic effects on new and improved product development within smaller firms has received less attention. Drawing on the knowledge-based view (KBV), we posit that innovation strategy plays an instrumental role in linking the effects of knowledge workers, thereby leading to greater product development outcomes from different types of knowledge workers. Moreover, some suggest that beyond a certain point, there is a diminishing return to increasing the proportion of knowledge workers in an organisation; however, the basis of this finding is within larger firms. This study investigates whether high-level (e.g. engineers and scientists) and low-level (e.g. technicians and machine operators) knowledge workers exert varying effects on performance in terms of new and improved product development. Data from 205 small and medium-sized high-tech manufacturing firms provide support that distinguishing among types of knowledge workers is important given that they impact new and improved product development differently. Furthermore, innovation strategy plays a synergistic role, positively mediating the effects of different types of knowledge workers on innovation outcomes.